Advancements in the digital image acquisition techniques such as ultrasound (US), computed tomography (CT), magnetic resonance (MR), positron emission tomography (PET), positron emission tomography-computed tomography (PET-CT) and single photon emission computed tomography (SPECT) that allow detecting and visualizing tumour lesions are still ongoing. The overall objective is to increase the accuracy of the images acquired. The main motivation therefore is that residual hot spots in malignant lesions can still remain undetected, possibly leaving one or more very aggressive tumoural cells in the patient, even in case of regressive therapy response. The detection of such hot spots through improved image acquisition and post-processing is important because patients with residual hot spots are not tumour-free as a result of which their prognosis has not improved meaningfully. The patient's prognosis improves meaningfully only if all tumoural cells are destroyed.
United States patent application US 2003/0211036, entitled “Method and Apparatus for Monitoring and Quantitatively Evaluating Tumour Perfusion” from the inventors Degani et al., describes the use of a non-toxic tracer based solution such as deuterated labelled water (HDO) to monitor and evaluate response to tumour therapy. The method described in US 2003/0211036 is based on quantifying tissue perfusion and uses non-invasive MRI based imaging to monitor the response to therapy. US 2003/0211036 recognizes the problem of heterogeneity of tumours and the need for increased accuracy of the images obtained. In order to overcome this problem, a perfusion based method that increases the spatial resolution is presented in US 2003/0211036. As is illustrated by FIG. 6 of US 2003/0211036, processed data retain the same resolution as acquired data. US 2003/0211036 consequently shows the advantage of using HDO over macromolecules as a tracer in perfusion based technique. It allows observing voxels in which flow is rate limiting as well as voxels in which contributions from capillary permeability affect the process of perfusion, thereby enhancing the accuracy.
US 2003/0211036 recognizes that a number of different perfusion related parameters such as the perfusion rate or the parameter K allow the determination of hot spots that are highly perfused. They also allow evaluation of the perfusion in voxels that are poorly perfused. Further, the significance of involvement of the intravascular volume fraction vp in perfusion based analysis is demonstrated in US 2003/0211036. At last, US 2003/0211036 also reveals the importance of processing the data at high resolution. Low resolution analysis averages the perfusion information resulting in loss of very high and very low values, thereby losing residual hot spots. The spatially degraded maps in US 2003/0211036 represent tumour slices with 1-2 voxels in the region of interest (ROI). Obtaining the mean values of high resolution data as well as the actual values of degraded resolution does not reflect the actual heterogeneity of the perfusion parameters. Therefore, US 2003/0211036 concludes the importance of monitoring and processing perfusion at high spatial resolution and using parametric maps or images that are colour coded for visual inspection of the spatial distribution.
The method known from US 2003/0211036 however suffers from several disadvantages that will be explained in the following paragraphs.
Firstly, US 2003/0211036 suggests the use of specific perfusion parameters that have been shown to be essential in solving the resolution based problems of the images. The effect of the diffusion of the tracer based solution is not addressed.
Secondly, the values for the voxels within the region of interest are averaged for the high resolution data and low resolution data. Such an approach results in loss of hot spots, and US 2003/0211036 fails to seek further improvements to this problem.
In summary, the method known from US 2003/0211036 recognizes but does not adequately solve the resolution problem. The possibility to accurately indicate and visualize quantitative changes in functional parameters such as true diffusion values and perfusion factor over a period of time is still missing. As a result, residual malignant tumour cells that are therapy-resistant are not detected and efficient prognosis of therapy response by the physician remains difficult or impossible.
The article “Assessing changes in tumour vascular function using dynamic contrast-enhanced magnetic resonance imaging” from the authors Carmel Hayes, Anwar R. Padhani and Martin O. Leach describes the use of dynamic contrast-enhanced DCE-MRI based quantitative and qualitative methods to evaluate the response to chemotherapy. Changes in the temporal pattern of signal enhancement, the rate and amplitude of enhancement and the volume transfer constant of contrast agent between the blood plasma and the extravascular extracellular space (EES), Ktrans and the EES fractional volume, ve, were determined. Whole tumour region of interest analysed is compared with histogram based analysis in this article to investigate the impact of tumour heterogeneity. FIG. 6-FIG. 10 of the article of Hayes et al. compare the use of median values with pre- and post-treatment Ktrans values for whole tumour ROI analysis. The article shows that changes in Ktrans values for hot spots differ considerably from whole tumour averaged values.
The above mentioned article from C. Hayes et al. pertains to understand the characteristics of tumour microvasculature that play a role in the treatment of cancer. The article compares whole tumour region-of-interest analysis with histogram analysis and investigates the sensitivities of different methods. The article concludes that a higher median Ktrans value is more likely to respond to chemotherapy and that vascular permeability has a role to play in the delivery and efficacy of chemotherapeutic agents. By increasing the permeability of the tumours vasculature, selective drug delivery may be achieved. On the contrary, the chemotherapeutic agents give rise to reduction in Ktrans due to antivascular effect or due to tumour cell death. Although the article addresses the problem of whole tumour region-of-interest averaging, the article fails to teach a solution for improving the accuracy of evaluating tumour evolution through post-processing of temporal images.
In another article from the authors Bradford A. Moffat, Thomas L. Chenevert, Charles R. Meyer, Paul E. McKeever, Daniel E. Hall, Benjamin A. Hoff, Timothy D. Johnson, Alnawaz Rehemtulla and Brian D. Ross, entitled “The Functional Diffusion Map: An Imaging Biomarker for the Early Prediction of Cancer Treatment Outcome”, an imaging technique for early prediction of brain tumour treatment efficacy is described. The technique quantifies the treatment induced changes in tumour water diffusion. The MRI-based approach described in this article spatially maps and quantifies treatment-induced changes in the tumour's water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. The article further introduces co-registration of images using a MIAMI Fuse based algorithm. Changes in apparent diffusion coefficient value (ADC) are visualized using colour codes such as red (increased ADC values above an upper threshold), blue (decreased ADC values below a lower threshold) or green (tumour voxels whose ADC values show changes in between the two thresholds) for early prediction of treatment efficacy. The residual hot spots are depicted in a voxel/pixel like manner. This is illustrated by FIG. 2 of the article.
The above article generally deals with the use of biomarkers that are sensitive to confirm drug activity and can be generalized to alternative functional parameters such as Ktrans. Although automated, colour-coded voxel/pixel wise quantification of functional parameters allows follow-up of oncologic patients and enables evaluation of the presence respectively absence of response to therapy, the generated images are noisy and difficult to interpret by the physician.
In summary, existing methods for evaluating the evolution of tumoural lesions rely on averaged functional values, either perfusion or diffusion parameters, for the complete tumour region. Although these methods are quantitative, they may not show significant changes and definitely fail to quantify and visualize the heterogeneity of the tumour evolution, leaving for instance residual hot spots invisible for the physician. Alternative known techniques for the evaluation of tumour evolution are based on voxel/pixel wise calculation and coding of functional parameters. These techniques generally fail to provide quantitative output, and the produced images are difficult to interpret rapidly and accurately by physicians as a result of which they are of poor value for clinical practice.
It is an objective of the present invention to provide a method and device for evaluating the evolution of tumoural lesions that overcomes the above mentioned shortcomings of prior art solutions. In particular, it is an objective of the current invention to provide a usable method and tool for clinical applications that enables physicians to rapidly and accurately assess the response to therapy, drugs, etc., taking into account the heterogeneity of tumour evolution and minimizing the risk of leaving residual hot spots unnoticed.